论文标题
Climatenerf：神经辐射场中的极端天气综合
ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field
论文作者
论文摘要
物理模拟可以很好地预测天气影响。神经辐射场产生SOTA场景模型。我们描述了一种新颖的NERF编辑程序，该程序可以将物理模拟与场景的NERF模型融合在一起，从而在这些场景中产生现实的物理现象电影。我们的应用程序 - 气候nerf-允许人们可视化气候变化结果对它们的影响。 Climatenerf允许我们对逼真的天气影响，包括烟雾，雪和洪水。结果可以通过像水位这样的物理有意义的变量来控制。定性和定量研究表明，我们的模拟结果比SOTA 2D图像编辑和SOTA 3D NERF风格化的结果明显更现实。
Physical simulations produce excellent predictions of weather effects. Neural radiance fields produce SOTA scene models. We describe a novel NeRF-editing procedure that can fuse physical simulations with NeRF models of scenes, producing realistic movies of physical phenomena in those scenes. Our application -- Climate NeRF -- allows people to visualize what climate change outcomes will do to them. ClimateNeRF allows us to render realistic weather effects, including smog, snow, and flood. Results can be controlled with physically meaningful variables like water level. Qualitative and quantitative studies show that our simulated results are significantly more realistic than those from SOTA 2D image editing and SOTA 3D NeRF stylization.
